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Generalized Joint Signal Representations and Optimum Detection

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Title: Generalized Joint Signal Representations and Optimum Detection
Author: Sayeed, Akbar M.; Jones, Douglas L.
Type: Conference Paper
Keywords: Joint Signal Representations; Unitary Operator Covariance; Nonstationarity; Quadratic Detection
Citation: A. M. Sayeed and D. L. Jones,"Generalized Joint Signal Representations and Optimum Detection," in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),
Abstract: Generalized joint signal representations (JSRs) extend the scope of joint time-frequency representations (TFRs) to a richer class of nonstationary signals, but their use, just as in the case of TFRs, has been primarily limited to qualitative, exploratory data analysis. To exploit their potential more fully, JSR-based statistical signal processing techniques need to be developed that can be successfully applied in real-world problems. In this paper, we present an optimal detection framework based on arbitrary generalized quadratic JSRs, thereby making it applicable in a wide variety of detection scenarios involving nonstationary stochastic signals, noise and interference. For any given class of generalized JSRs, we characterize the corresponding class of detection scenarios for which such JSRs constitute canonical detectors, and derive the corresponding JSR-based detectors. Our formulation also yields a very useful subspace-based interpretation in terms of corresponding linear JSRs that we exploit to design optimal detectors based on only partial signal information.
Date Published: 1996-01-20

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  • ECE Publications [1046 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.